Writing and call functions in Python is a fundamental skill that transforms repetitive code into clean, reusable blocks of logic. Functions allow you to encapsulate specific tasks with a name, making your code more organized and easier to understand. By using the def keyword, you define what a function does, and by calling it with its name followed by parentheses, you trigger that behavior whenever needed.

Whether calculating a value, processing input, or returning results, functions let you structure your code with clarity and purpose. Mastering this concept opens the door to building more efficient and modular Python programs. In this article, I’ll walk you through defining and calling the Python main function, helping you break your Python applications into smaller, more manageable chunks. I’ll also explain how arguments and the return keyword function within Python enhance code flexibility and efficiency.

What Is a Function?

A function is a named block of code designed to carry out a specific task. After it’s defined, students can reuse this code multiple times without having to rewrite the same code. Functions are useful for breaking down large programs into smaller, more manageable sections.

Python Function List From Our Python Homework Help Team  

Check out this handy Python function list from our Python homework help team—perfect for quick reference and improving your coding and assignment skills.

Basic Built-in Functions

1. print() – Displays output to the console
2. len() – Returns the length of an object (e.g., string, list)
3. type() – Returns the type of an object
4. int(), float(), str() – Type conversions
5. input() – Takes user input as a string
6. range() – Generates a sequence of numbers

Data Handling Functions

1. sum() – Adds all elements in an iterable
2. min(), max() – Returns the smallest or largest value
3. sorted() – Returns a sorted list
4. list(), tuple(), set(), dict() – Converts to respective data types

Functional Programming Tools

1. map() – Applies a function to each item in an iterable
2. filter() – Filters elements based on a condition
3. zip() – Combines multiple iterables into tuples
4. enumerate() – Adds an index to items in an iterable

Utility Functions

1. abs() – Returns the absolute value
2. round() – Rounds a number to the nearest integer or given decimals
3. divmod() – Returns a tuple of quotient and remainder
4. all() – Returns True if all items in an iterable are true
5. any() – Returns True if at least one item is true

Advanced Tools

1. eval() – Executes a string as Python code (use with caution)
2. exec() – Executes dynamic Python code
3. id() – Returns the memory address of an object
4. help() – Provides documentation on objects or modules

Why Do We Use Functions in Python? – Key Reasons Explained

Functions are among the most powerful and essential building blocks in any programming language, and Python is no exception. Whether you’re automating tasks, solving complex problems, or simply organizing your code better, functions play a central role. Here’s a deep dive into why we use functions in Python, supported by key pointers:

Code Reusability

Functions allow you to write code once and reuse it as many times as needed. Instead of repeating blocks of code throughout your program, you can define a function and call it wherever required. This reduces redundancy and keeps your code DRY (Don’t Repeat Yourself).

Modularity and Organisation

Functions help break down large, complex problems into smaller, manageable parts. Each function can be responsible for a specific task, making the code easier to write, read, test, and maintain. Consider turning a long essay into organised paragraphs, each serving its purpose.

Improved Testing and Debugging

When your code is divided into functions, you can test them individually (unit testing). If there’s an error, you can focus on the faulty function rather than scanning an entire script.

For example: You can test a calculate_tax() function independently from your entire billing application.

Better Readability

Functions add structure and meaning to your code. When a function is named well (like calculate_total()), it conveys what the block of code does, making it easier for others (and your future self) to understand it quickly.

Function Parameters Make Code Flexible

Functions can take parameters to perform tasks on dynamic input. This means your logic becomes more general-purpose and adaptable to different use cases.

Boosts Productivity

By encapsulating frequently used operations into functions, you speed up development. Writing less and clearer code helps you deliver solutions faster.

Encapsulation and Abstraction

Functions allow you to hide complex logic behind a simple interface. This means the user of the function doesn’t need to understand how it works—just what it does. This is key in building APIs or tools for others.

Foundation for Advanced Concepts

Understanding functions is crucial for learning object-oriented programming, recursion, lambda functions, and higher-order functions in Python. They are the gateway to writing scalable and advanced applications.

Basic Syntax for Defining a Function in Python

In Python, defining a function starts with the def keyword, followed by the function name and a set of parentheses that may include parameters. The function header ends with a colon. The indented block that follows the colon contains the function’s code, known as the body. Optionally, a programmer uses the return statement to send back a result from the function.

For example, def add(a, b): return a + b defines a simple function that adds two numbers. This structure allows you to reuse code efficiently and keep your programs organized and modular.

def is the keyword used to declare a function.

Function_name is the name you give to your function.

Parameters are optional inputs passed to the function.

return sends back the result (also optional).

The function body is indented and contains the code the function executes.

Basic Examples of a Function in Python

Basic examples of functions in Python showcase how versatile and useful they are when you are up for organising Python code. A simple function like def say_hello(): print(“Hello, world!”) performs a task without requiring any input, while def greet(name): print(f”Hello, {name}!”) accepts a parameter and personalises the output. Functions can also return values, as seen in def add(a, b): return a + b, making them essential for performing calculations and reusing logic throughout your program.

Here are a few basic examples of functions in Python to illustrate how they work. These examples highlight how functions help break down tasks into manageable parts, improving readability and maintainability.

1. Function without parameters:

Call it with:

2. Function with parameters:

Call it with:

3. Function with return value:

Call it with:

These examples demonstrate how you can use these Python functions to organize and reuse code effectively.

Arguments in Python Functions

Arguments in Python functions are the values passed to a function when called, allowing it to perform operations based on that input. Functions can accept any number of arguments, which are defined as parameters in the function definition. For example, in def multiply(a, b): return a * b, a and b are parameters, and when you call multiply(2, 3), the values 2 and 3 are the arguments. Python also supports default, keyword, and variable-length arguments, giving you flexibility in designing and calling your functions. Understanding the effective usage of arguments is key to writing dynamic and reusable code.

Positional Arguments – Matched by order:

Keyword Arguments – Matched by name:

Default Arguments – Provide default values:

Variable-Length Arguments – Accept multiple values:

• *args for non-keyword arguments:

**kwargs for keyword arguments:

N.B.: You can specify as many arguments as you want.

Understanding these allows for flexible and powerful function definitions in Python.

How to Use the Return Keyword in Python

The return keyword in Python is used within a function to send the result back to the part of the program that called the function. It not only ends the function’s execution but also provides the specified value to the caller, enabling further use or storage of the output. Here, I have used examples to help students better comprehend the concept.

For instance, in def square(x): return x * x, calling square(5) will return 25, which can then be assigned to a variable or printed directly. You can also return multiple values by separating them with commas, which Python automatically packs into a tuple. Using return effectively allows for more dynamic, reusable, and maintainable code.

When you call square(4), it returns 16, which you can store in a variable or use directly:

You can also return multiple values as a tuple:

What’s the code above doing?

• I have defined a function and named it multiplyNum. Also, passed num1 as its argument.
• I used the return keyword inside the function to multiply num1 by 8.
• Then, I called the function with 8 as the value of the num1 argument and stored the result in a variable named result.
• Finally, I used the result variable to display the outcome of the function in the terminal.

Using return helps keep your code modular and reusable by allowing functions to provide output instead of just acting.

Conclusion

Mastering how to write and call functions in Python is essential for students, especially when aiming to develop efficient, readable, and maintainable code. With the help of the functions I have discussed in this blog, students can break down complex problems into smaller, more manageable tasks. Using functions not only allows you to reuse code efficiently but also improves the structure of your programs. Experts recommend that students gain an in-depth understanding of functions for writing smarter and more scalable Python applications. You can automate calculations, process data, or return results more proficiently. 

With practice, using functions becomes second nature and a powerful asset in your programming toolkit. Our experts who help in Python have stated an effective method for practicing. They suggest you begin with simple steps. Then you must practice regularly, and soon you’ll be developing complex programs with well-organized functions like a pro!  However, if you are still struggling and need assistance from subject experts, opting for “do my Python assignment” from TutorBin is a more effective way to learn and excel in the CS language.  

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